Enhancement of panoramic musculoskeletal ultrasound image based on fuzzy technique

S. I. Jabbar, C. Day, E. Chadwick
{"title":"Enhancement of panoramic musculoskeletal ultrasound image based on fuzzy technique","authors":"S. I. Jabbar, C. Day, E. Chadwick","doi":"10.1145/3321289.3321312","DOIUrl":null,"url":null,"abstract":"Panoramic Musculoskeletal Ultrasound Images (PMUI) is a developed version of ultrasound images. However, low contrast is a concrete problem which impact negatively on the interpretation of important details of PMUI. Therefore, in this paper a new automated contrast enhancement method was presented and examined on the PMUI. A fuzzy technique is the main tool underpinning this method, and it consists of three steps: fuzzification, modification of membership equation and defuzzification. Maximum fuzzy entropy of PMUI was used to optimize parameters of the membership function. The quality of results was examined using quantitative metrics. Based on these assessment metrics, the performance of the fuzzy technique outperforms the performance of other method with 21%. The results achieved are very effective and could be used for preprocessing in computer vision applications.","PeriodicalId":375095,"journal":{"name":"Proceedings of the International Conference on Information and Communication Technology - ICICT '19","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Information and Communication Technology - ICICT '19","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3321289.3321312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Panoramic Musculoskeletal Ultrasound Images (PMUI) is a developed version of ultrasound images. However, low contrast is a concrete problem which impact negatively on the interpretation of important details of PMUI. Therefore, in this paper a new automated contrast enhancement method was presented and examined on the PMUI. A fuzzy technique is the main tool underpinning this method, and it consists of three steps: fuzzification, modification of membership equation and defuzzification. Maximum fuzzy entropy of PMUI was used to optimize parameters of the membership function. The quality of results was examined using quantitative metrics. Based on these assessment metrics, the performance of the fuzzy technique outperforms the performance of other method with 21%. The results achieved are very effective and could be used for preprocessing in computer vision applications.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于模糊技术的全景肌肉骨骼超声图像增强
全景肌肉骨骼超声图像(PMUI)是超声图像的发展版本。然而,低对比度是影响PMUI重要细节解释的一个具体问题。为此,本文提出了一种新的自动对比度增强方法,并在PMUI上进行了实验研究。该方法主要包括模糊化、隶属度方程修正和去模糊化三个步骤。利用PMUI的最大模糊熵对隶属函数参数进行优化。结果质量采用定量指标进行检验。基于这些评价指标,模糊技术的性能优于其他方法的性能21%。所得结果非常有效,可用于计算机视觉应用的预处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Security in telehealth applications: issues in medical image watermarking scheme through the shearlet transform A framework to optimize the frame duration and the beam angle for random beamforming of mmWave mobile networks Energy and RSSI based fuzzy inference system for cluster head selection in wireless sensor networks Dispersion characteristics of asymmetric multistep titanium nitride channel plasmon waveguide The effects of EEG feature extraction using multi-wavelet decomposition for mental tasks classification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1